Radius Intelligence Implements Databricks Cloud for Big Data Processing

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Databricks — the company founded by the creators of the popular open-source Big Data processing engine Apache Spark with its flagship product, Databricks Cloud — today announced that Radius Intelligence, the business-to-business marketing intelligence company, selected Databricks Cloud as its preferred big-data processing platform. Radius switched to the real-time Databricks Cloud platform to maximize throughput, speed and engineer productivity to help its customers realize the platform’s vision of true targeted marketing.

On a daily basis, Radius processes billions of data points from customers and external data sources to help marketers deploy targeted campaigns and predict future marketing and campaign success. The Radius team initially implemented the process of matching and harmonizing their data sets in Hadoop but found the solution hampered IT effectiveness, was too slow to handle increased code maintainability demands and bottlenecked the company’s ability to test new solutions.

Databricks Cloud was chosen as it is a solution that can overcome these challenges in a single unified platform by leveraging the power of Apache Spark. Radius was able to fully harness the power of Spark by deploying Databricks Cloud to maintain their Spark infrastructure, and to provide additional critical data analytics components on top of Spark, including:

  • Fully managed Spark clusters in the cloud that help enterprises focus on their data and not operations.
  • An interactive workspace for exploration and visualization so teams can learn, work and collaborate in a single, easy to use environment.
  • An extensible platform that enables organizations to connect their existing data applications with Spark to disseminate the power of big data.

By deploying Databricks Cloud, Radius and its customers have enjoyed tangible benefits. For instance, Radius’ core data index now takes only a few hours to build, while the same task previously took over a day to complete. Additionally, Radius teams have seen dramatic increases in overall effectiveness and can now work together to test hypotheses in real-time rather than over the course of several days.

In today’s marketing landscape, the number of data sources and the demand for speed are exploding. For instance, our customers recently began demanding weekly updates of our intelligence on over 25 million businesses in the US, as opposed to monthly updates,” explained Darian Shirazi, CEO of Radius Intelligence. “Without Databricks Cloud and the real-time insights from Spark, we wouldn’t be able to maintain our database at the pace needed for our customers to uncover hidden opportunities, maximize conversion rates and become the modern, targeted marketers they want to be.”

The combination of Spark’s speed and Databricks Cloud’s rich set of tools has allowed the Radius team to maximize the throughput and speed of data processing, which enables their engineering teams to acquire new capabilities that were not previously possible with Hadoop on Cloudera or Amazon EMR, such as:

  • Iterate running code in the Databricks Cloud interactive workspace (as opposed to Hadoop’s batch model) and receive results in minutes or even seconds. In contrast, doing this with Hadoop’s batch model required them to constantly create code, jar it and run it end to end on the server.
  • Visualize results of changes to the core matching technology without having to wait an entire day to receive results.
  • Allow collaboration with multiple teams on larger projects.

It’s always exciting to see Spark’s processing speed and power prove its enterprise value. Radius Intelligence is an impactful and innovative company that provides data, value and support to lots of leading customers,” said Ion Stoica, CEO of Databricks. “We’re thrilled to be able to provide similar support, from Spark deployment to ongoing management to additional analytics components on top of Spark, to Radius to help them continue to achieve that goal.”

Download the Radius case study here: https://databricks.com/customer-case-studies


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